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In this paper, we present a seq2seq approach for transliterating missionaryBasaa orthographies into the official orthography. Our model uses pre-trainedBasaa missionary and official orthography corpora using BERT. Since Basaa is alow-resource language, we have decided to use the mT5 model for our project.Before training our model, we pre-processed our corpora by eliminatingone-to-one correspondences between spellings and unifying characters variablycontaining either one to two characters into single-character form. Our bestmT5 model achieved a CER equal to 12.6747 and a WER equal to 40.1012.

Tone prediction and orthographic conversion for Basaa